Audience

Businesses seeking a tool to optimize ML models with real-time monitoring of training metrics and system resources

About Amazon SageMaker Debugger

Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values.

Integrations

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Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/debugger/

Videos and Screen Captures

Amazon SageMaker Debugger Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Webinars
Videos
Support
24/7 Live Support
Online

Amazon SageMaker Debugger Frequently Asked Questions

Q: What kinds of users and organization types does Amazon SageMaker Debugger work with?
Q: What languages does Amazon SageMaker Debugger support in their product?
Q: What kind of support options does Amazon SageMaker Debugger offer?
Q: What other applications or services does Amazon SageMaker Debugger integrate with?
Q: What type of training does Amazon SageMaker Debugger provide?

Amazon SageMaker Debugger Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization
Statistical / Mathematical Tools